Triple
T12597462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | classical fourth-order Runge–Kutta method |
E300768
|
entity |
| Predicate | usesWeightedAverageOfSlopes |
P105623
|
FINISHED |
| Object | (k1 + 2 k2 + 2 k3 + k4) / 6 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: (k1 + 2 k2 + 2 k3 + k4) / 6 | Statement: [classical fourth-order Runge–Kutta method, usesWeightedAverageOfSlopes, (k1 + 2 k2 + 2 k3 + k4) / 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWeightedAverageOfSlopes Context triple: [classical fourth-order Runge–Kutta method, usesWeightedAverageOfSlopes, (k1 + 2 k2 + 2 k3 + k4) / 6]
-
A.
slopeUse
Indicates how a particular slope or gradient is utilized or purposed in relation to another entity.
-
B.
isOnSlopeOf
Indicates that one entity is located on the inclined surface or side of another entity, typically a sloping terrain or structure.
-
C.
hasSlopeFeature
Indicates that an entity possesses or is characterized by a particular slope-related property or feature.
-
D.
averageGradient
Indicates the mean rate of change (slope) of a quantity over a specified interval or region.
-
E.
slopeType
Indicates the classification of a slope based on its geometric or physical characteristics, such as steepness, shape, or orientation.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954e351f88190869220d46e0ce282 |
completed | April 10, 2026, 7:52 p.m. |
Created at: April 9, 2026, 5:08 p.m.